A novel method of battery state-of-health estimation for energy storage station based on inconsistency and dual time-scale extended Kalman filtering

• DOI: 10.1109/ecce53617.2023.10362483
• Publication Date: 2023-12-29T19:27:17Z
• Authors: Jiahao Zhang; Xianmin Mu; Zhaoyuan Huang; Fanpeng Zeng; Jing Liu; Guanlin Li

In order to obtain battery cells' state-of-health (SOH), dual extended Kalman filter (DEKF)based on equivalent circuit model (ECM)is employed frequently. However, sensitive initial setup, the above method's estimator is prone divergence, and cost heavy computation effort so that doesn't meet demand in energy storage station. This paper presents a new method determine SOHs of cells series-connected pack. The reference battery's state-of-charge (SOC)is calculated by using cell (CRM), then we based difference (CDM) figure out internal resistance capacity other cells, innovatively explore health information from voltage response differences different battery. We conduct an experiment real data set with four connected series verify algorithm, results show proposed algorithm has lower computational cost, high parameter identification stability, simple setting, good performance.